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Finance Seminar

Authors:

• Byoung-Hyoun Hwang
  Purdue University

• Dong Lou
  Purdue University

This paper tests the hypothesis that analysts report biased earnings estimates in order to enhance their stock recommendation performance. In particular, we propose that analysts with optimistic (pessimistic) stock recommendations may issue negatively (positively) biased earnings forecasts so that the firm is more likely to beat (miss) the consensus forecast and experience higher (lower) stock returns. Consistent with this hypothesis, we find that stock recommendations prior to earnings announcements significantly and positively predict subsequent earnings forecast errors, and that such predictability is substantially stronger when the net benefits associated with such strategic behavior are larger. Moreover, while recommendation levels do not predict stock returns unconditionally, they significantly and positively predict returns around earnings announcements.